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首页> 外文期刊>The Science of the Total Environment >Changes in China's carbon footprint and driving factors based on newly constructed time series input-output tables from 2009 to 2016
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Changes in China's carbon footprint and driving factors based on newly constructed time series input-output tables from 2009 to 2016

机译：基于新构建的时间序列投入产出表，2009年至2016年中国碳足迹和驱动因素的变化

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China is the country with the most carbon emissions and the largest foreign trade volume worldwide. China's carbon footprint, especially the carbon footprint of exports, must be studied to clarify China's responsibility for carbon emissions, avoid "carbon leakage" and develop more reasonable emission reduction policies. By comparing 6 update models, this paper adopts the GRAS, which is a typical entropy optimization method for matrix updating, to construct new time series input-output (IO) tables for China from 2009 to 2016 to analyze the carbon footprint of China's domestic final demand and exports. Then, the changes in the footprints were investigated with a structural decomposition analysis (SDA) to determine the driving factors. The carbon footprint of exports showed an upward trend from 2009 to 2012 and a downward trend from 2012 to 2016. The export share of the total consumption-based carbon footprint also increased from 2009 (17.64%) to 2012 (21.47%) and then decreased to 16.40% in 2016, reflecting a reduction in the CO_2 emissions transferred to China after 2013. According to the SDA results, the emission intensity effect (664.20 Mt CO_2) and primary input effect (555.21 Mt CO_2) played a key role in reducing the carbon footprint, and the total export effect (1083.12 Mt CO_2) contributed the most to the increase in the carbon footprint of exports. Based on further SDA, the effects of the primary input, Leontief structure and export structure dramatically varied based on China's industrial structure adjustment and technological change during the subperiod. The analysis framework and data in this paper can be applied to further study China's energy economy and environmental issues.
机译：中国是世界上碳排放量最大，对外贸易额最大的国家。必须研究中国的碳足迹，尤其是出口的碳足迹，以阐明中国对碳排放的责任，避免“碳泄漏”并制定更合理的减排政策。通过比较6种更新模型，本文采用GRAS（一种用于矩阵更新的典型熵优化方法）构建了2009年至2016年中国新的时间序列投入产出表，以分析中国国内最终排放量的碳足迹。需求和出口。然后，通过结构分解分析（SDA）研究足迹的变化，以确定驱动因素。从2009年到2012年，出口的碳足迹呈上升趋势，从2012年到2016年呈下降趋势。出口占总消费型碳足迹的份额也从2009年（17.64％）上升至2012年（21.47％），然后下降到2016年降至16.40％，反映出2013年后转移到中国的CO_2排放量减少。根据SDA结果，排放强度效应（664.20 Mt CO_2）和主要投入效应（555.21 Mt CO_2）在减少二氧化碳排放量方面发挥了关键作用。碳足迹以及总出口效应（1083.12 Mt CO_2）对出口碳足迹的增加贡献最大。在进一步的SDA的基础上，次时期中国的产业结构调整和技术变化会影响主要投入，列昂蒂夫结构和出口结构的变化。本文的分析框架和数据可用于进一步研究中国的能源经济和环境问题。

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